title: Accelerating k-t sparse using k-space aliasing for dynamic MRI imaging.
abstract: Dynamic imaging is challenging in MRI and acceleration techniques are usually needed to acquire dynamic scene. K-t sparse is an acceleration technique based on compressed sensing, it acquires fewer amounts of data in k-t space by pseudo random ordering of phase encodes and reconstructs dynamic scene by exploiting sparsity of k-t space in transform domain. Another recently introduced technique accelerates dynamic MRI scans by acquiring k-space data in aliased form. K-space aliasing technique uses multiple RF excitation pulses to deliberately acquire aliased k-space data. During reconstruction a simple Fourier transformation along time frames can unaliase the acquired aliased data. This paper presents a novel method to combine k-t sparse and k-space aliasing to achieve higher acceleration than each of the individual technique alone. In this particular combination, a very critical factor of compressed sensing, the ratio of the number of acquired phase encodes to the number of total phase encode (n/N) increases therefore compressed sensing component of reconstruction performs exceptionally well. Comparison of k-t sparse and the proposed technique for acceleration factors of 4, 6 and 8 is demonstrated in simulation on cardiac data.
authors.forename: Kamlesh
authors.initials: K
authors.lastname: Pawar
authors.forename: Gary F
authors.initials: GF
authors.lastname: Egan
authors.forename: Jingxin
authors.initials: J
authors.lastname: Zhang
mesh_terms: D000054:Acceleration; D000465:Algorithms; D003198:Computer Simulation; D006801:Humans; D007091:Image Processing, Computer-Assisted; D008279:Magnetic Resonance Imaging / Q000379:methods*; D013997:Time Factors